scholarly journals The Art of Positronics in Contemporary Nanomaterials Science: A Case Study of Sub-Nanometer Scaled Glassy Arsenoselenides

Materials ◽  
2022 ◽  
Vol 15 (1) ◽  
pp. 302
Author(s):  
Oleh Shpotyuk ◽  
Adam Ingram ◽  
Catherine Boussard-Pledel ◽  
Bruno Bureau ◽  
Zdenka Lukáčová Bujňáková ◽  
...  

The possibilities surrounding positronics, a versatile noninvasive tool employing annihilating positrons to probe atomic-deficient sub-nanometric imperfections in a condensed matter, are analyzed in application to glassy arsenoselenides g-AsxSe100−x (0 < x < 65), subjected to dry and wet (in 0.5% PVP water solution) nanomilling. A preliminary analysis was performed within a modified two-state simple trapping model (STM), assuming slight contributions from bound positron–electron (Ps, positronium) states. Positron trapping in g-AsxSe100−x/PVP nanocomposites was modified by an enriched population of Ps-decay sites in PVP. This was proven within a three-state STM, assuming two additive inputs in an overall trapping arising from distinct positron and Ps-related states. Formalism of x3-x2-CDA (coupling decomposition algorithm), describing the conversion of Ps-decay sites into positron traps, was applied to identify volumetric nanostructurization in wet-milled g-As-Se, with respect to dry-milled ones. Under wet nanomilling, the Ps-decay sites stabilized in inter-particle triple junctions filled with PVP replaced positron traps in dry-milled substances, the latter corresponding to multi-atomic vacancies in mostly negative environments of Se atoms. With increased Se content, these traps were agglomerated due to an abundant amount of Se-Se bonds. Three-component lifetime spectra with nanostructurally- and compositionally-tuned Ps-decay inputs and average lifetimes serve as a basis to correctly understand the specific “rainbow” effects observed in the row from pelletized PVP to wet-milled, dry-milled, and unmilled samples.

Author(s):  
Jifeng Chen ◽  
Peilin Song ◽  
Thomas M. Shaw ◽  
Franco Stellari ◽  
Lynne Gignac ◽  
...  

Abstract In this paper, we propose a new methodology and test system to enable the early detection and precise localization of Time-Dependent-Dielectric-Breakdown (TDDB) occurrence in Back-End-of-Line (BEOL) interconnection. The methodology is implemented as a novel Integrated Reliability Test System (IRTS). In particular, through our methodology and test system, we can easily synchronize electrical measurements and emission microscopy images to gather more accurate information and thereby gain insight into the nature of the defects and their relationship to chip manufacturing steps and materials, so that we can ultimately better engineer these steps for higher reliable systems. The details of our IRTS will be presented along with a case study and preliminary analysis results.


1986 ◽  
Vol 3 (5) ◽  
pp. 237-240 ◽  
Author(s):  
Xiong Liangyue (L Y Xiong)

Fisheries ◽  
2020 ◽  
Vol 2020 (1) ◽  
pp. 66-70
Author(s):  
Yuri Simakov ◽  
Dmitry Nikiforov-Nikishin ◽  
Larisa Bychkova ◽  
Nadegda Lyubovskaya

The results of laboratory experiments on nitroglycerine toxicity detected by histological and cytological indices are presented, using Danio rerio as a case study. For the first time, there are shown the changes in liver and kidneys, both at tissular and cellular levels, induced by administered concentrations of nitroglycerine. The results obtained appear to be important for water bodies’ preservation and elaboration of MPC standards. The intake of nitroglycerine into water bodies is due, mainly, to discharge from pharmaceutical enterprises, demolition works, and outflow from explosives storehouses. Fish turned out to be sensitive to nitroglycerine as indicated by histological and hematological indices. Maximum permissible concentration, MPC, for Danio rerio is determined to be equal to 0.5 mg/l.


2017 ◽  
Vol 10 ◽  
pp. 292-301 ◽  
Author(s):  
Bayu Rudiyanto ◽  
IbnuAtho Illah ◽  
Nugroho Agung Pambudi ◽  
Chin-Chi Cheng ◽  
Reza Adiprana ◽  
...  

2015 ◽  
Vol 9 (1) ◽  
pp. 30 ◽  
Author(s):  
María Messina ◽  
Esther Hochsztain

<p>El Centro de Emprendedurismo CCEEmprende de- sarrolla, desde 2007, un programa de apoyo a emprende- dores. Para mejorar su gestión, resulta de gran importancia analizar, en forma preliminar, los emprendimientos en una de dos categorías: éxito o fracaso. En este artículo se identifican los principales factores asociados al éxito de un emprendimiento y cómo se vincu- lan para anticipar el futuro del emprendimiento. Se presenta un caso de estudio con base en los datos de una encuesta realizada a emprendedores participantes del programa, aplicando técnicas de clasificación. Las dos técnicas utilizadas de data mining son árbol de decisión y regresión logística, en ambas se obtuvieron resultados coincidentes. Los hallazgos muestran que los dos elementos más relevantes para anticipar el éxito de un emprendimiento son contar con financiamiento y que, anteriormente, la situa- ción laboral del emprendedor sea trabajador independiente. Estos primeros resultados obtenidos en el estudio de caso revelan información útil acerca de las mejores formas de apoyo al emprendedor, cómo generar incentivos al em- prendedor y la definición de herramientas o actividades que incidan favorablemente en el éxito de los emprendimientos. Si bien desde la teoría o para otras realidades existe infor- mación sobre los factores que colaboran en la determina- ción del éxito, para la realidad del Uruguay no se identifican estudios similares.</p><p> </p><p><strong>Abstract</strong> </p><p>Since 2007, the CCEE Entrepreneurship Centre has developed a supporting program for entrepreneurs. A preliminary analysis to determine if the venture was successful or a failure is made to improve the program’s management . In this article, the authors identify the main factors associated with entrepreneurship’s success, and how they can anticipate entrepreneurship’s performance. The case study is based on a survey data applied to the Entrepreneurship Program participants. The two data mining techniques are decision trees and logistic regression. The results were consistent across both tech- niques. The findings show that the two most important elements to predict entrepreneurship’s success are fun- ding and previous experience as self-employed. The results provided very useful insight about the best ways to support entrepreneurship, how to encoura- ge entrepreneurs, and define tools or activities to impact positively ventures success in Uruguay, since similar stu- dies have not been developed.</p>


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